Bacterial Nanocellulose Hydrogel: A Promising Alternative Material for the Fabrication of Engineered Vascular Grafts
Bibliographic record
Abstract
Blood vessels are crucial in the human body, providing essential nutrients to all tissues while facilitating waste removal. As the incidence of cardiovascular disease rises, the demand for efficient treatments increases concurrently. Currently, the predominant interventions for cardiovascular disease are autografts and allografts. Although effective, they present limitations including high costs and inconsistent success rates. Recently, synthetic vascular grafts, made from artificial materials, have emerged as promising alternatives to traditional methods. Among these materials, bacterial cellulose hydrogel exhibits significant potential for tissue engineering applications, particularly in developing nanoscale platforms that regulate cell behavior and promote tissue regeneration, attributed to its notable physicochemical and biocompatible properties. This study reviews recent progress in fabricating engineered vascular grafts using bacterial nanocellulose, demonstrating the efficacy of bacterial cellulose hydrogel as a biomaterial for synthetic vascular grafts, specifically for stimulating angiogenesis and neovascularization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".